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BERT_with_preprocessing_grid_search

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update model card README.md

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@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7918
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- - Precision: 0.8374
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- - Recall: 0.8246
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- - F1: 0.8306
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- - Accuracy: 0.8645
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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- - train_batch_size: 32
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- - eval_batch_size: 32
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 255 | 0.7382 | 0.7058 | 0.7789 | 0.7260 | 0.7894 |
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- | 0.907 | 2.0 | 510 | 0.5794 | 0.7838 | 0.8189 | 0.7976 | 0.8444 |
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- | 0.907 | 3.0 | 765 | 0.5382 | 0.8084 | 0.8375 | 0.8200 | 0.8547 |
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- | 0.2877 | 4.0 | 1020 | 0.5942 | 0.8301 | 0.8319 | 0.8301 | 0.8670 |
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- | 0.2877 | 5.0 | 1275 | 0.6349 | 0.8198 | 0.8384 | 0.8280 | 0.8655 |
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- | 0.1513 | 6.0 | 1530 | 0.7735 | 0.8384 | 0.8144 | 0.8250 | 0.8635 |
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- | 0.1513 | 7.0 | 1785 | 0.7221 | 0.8456 | 0.8333 | 0.8385 | 0.8704 |
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- | 0.1059 | 8.0 | 2040 | 0.7615 | 0.8390 | 0.8312 | 0.8349 | 0.8684 |
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- | 0.1059 | 9.0 | 2295 | 0.7841 | 0.8362 | 0.8253 | 0.8306 | 0.8684 |
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- | 0.0811 | 10.0 | 2550 | 0.7918 | 0.8374 | 0.8246 | 0.8306 | 0.8645 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8836
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+ - Precision: 0.8262
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+ - Recall: 0.8258
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+ - F1: 0.8249
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+ - Accuracy: 0.8724
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 1.047 | 1.0 | 510 | 0.6171 | 0.7493 | 0.8057 | 0.7716 | 0.8336 |
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+ | 0.4348 | 2.0 | 1020 | 0.4954 | 0.8056 | 0.8646 | 0.8296 | 0.8714 |
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+ | 0.2818 | 3.0 | 1530 | 0.6252 | 0.8181 | 0.8323 | 0.8212 | 0.8660 |
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+ | 0.1793 | 4.0 | 2040 | 0.7381 | 0.8216 | 0.8258 | 0.8227 | 0.8733 |
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+ | 0.1356 | 5.0 | 2550 | 0.8601 | 0.8161 | 0.8219 | 0.8165 | 0.8660 |
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+ | 0.1023 | 6.0 | 3060 | 0.8526 | 0.8363 | 0.8299 | 0.8307 | 0.8758 |
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+ | 0.0944 | 7.0 | 3570 | 0.8459 | 0.8234 | 0.8298 | 0.8251 | 0.8729 |
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+ | 0.0631 | 8.0 | 4080 | 0.8519 | 0.8212 | 0.8325 | 0.8252 | 0.8714 |
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+ | 0.0602 | 9.0 | 4590 | 0.8756 | 0.8200 | 0.8267 | 0.8226 | 0.8719 |
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+ | 0.0532 | 10.0 | 5100 | 0.8836 | 0.8262 | 0.8258 | 0.8249 | 0.8724 |
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  ### Framework versions